Submission¶
Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
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from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
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#load data
df = px.data.gapminder()
df.head()
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| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Question 1:¶
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
- Extract the 2007 year data from the dataframe. You have to process the data accordingly
- use plotly bar
- Add different colors for different continents
- Sort the order of the continent for the visualisation. Use axis layout setting
- Add text to each bar that represents the population
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import plotly.express as px
import pandas as pd
df_2007 = df[df['year'] == 2007]
continent_pop = df_2007.groupby('continent')['pop'].sum().reset_index()
colors = {'Asia': 'red', 'Europe': 'blue', 'Africa': 'green', 'Americas': 'orange'}
fig = px.bar(
continent_pop,
x='continent',
y='pop',
color='continent',
color_discrete_map=colors,
labels={'pop': 'Population'},
title='Population of Continents in 2007')
fig.update_layout(
xaxis_title='Continent',
yaxis_title='Population',
showlegend=False)
fig.show()
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fig.update_layout(
xaxis=dict(categoryorder='array', categoryarray=['Asia', 'Africa', 'Americas', 'Europe', 'Oceania']),
xaxis_title='Continent',
yaxis_title='Population',
showlegend=False )
fig.show()
Question 3:¶
Add text to each bar that represents the population
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fig = px.bar(
continent_pop,
x='continent',
y='pop',
color='continent',
color_discrete_map=colors,
labels={'pop': 'Population'},
title='Population of Continents in 2007',
text='pop')
fig.show()
Question 4:¶
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
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df = px.data.gapminder()
fig = px.bar(
df,
x='continent',
y='pop',
color='continent',
labels={'continent': 'Continent', 'pop': 'Population'},
title='Population by Continent Over the Years',
animation_frame='year',
range_y=[0, df['pop'].max()])
fig.update_layout(xaxis={'categoryorder': 'total ascending'})
fig.show()
Question 5:¶
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
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df = px.data.gapminder()
fig = px.bar(
df,
x='country',
y='pop',
color='country',
labels={'country': 'Country', 'pop': 'Population'},
title='Population of Individual Countries Over the Years',
animation_frame='year',
range_y=[0, df['pop'].max()]
)
fig.update_layout(xaxis={'categoryorder': 'total ascending'})
fig.show()
Question 6:¶
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
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fig = px.bar(
df,
x='country',
y='pop',
color='country',
labels={'country': 'Country', 'pop': 'Population'},
title='Population of Individual Countries Over the Years',
animation_frame='year',
range_y=[0, df['pop'].max()]
)
fig.update_layout(
xaxis={'categoryorder': 'total ascending'},
height=1000)
fig.show()
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top_countries = df[df['year'] == df['year'].max()].nlargest(10, 'pop')
fig = px.bar(
df[df['country'].isin(top_countries['country'])],
x='country',
y='pop',
color='country',
labels={'country': 'Country', 'pop': 'Population'},
title='Top 10 Countries by Population Over the Years',
animation_frame='year',
range_y=[0, df['pop'].max()] )
fig.update_layout(xaxis={'categoryorder': 'total ascending'})
fig.update_layout(height=1000)
fig.show()
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